New research on tracking the location of smart phone users by monitoring power consumption:
#powerspy takes advantage of the fact that a phone’s cellular transmissions use more power to reach a given cell tower the farther it travels from that tower, or when obstacles like buildings or mountains block its #signal. That correlation between #battery use and variables like environmental conditions and cell tower distance is strong enough that momentary power drains like a phone conversation or the use of another power-hungry app can be filtered out, Michalevsky says.
One of the machine-learning tricks the researchers used to detect that “noise” is a focus on longer-term trends in the phone’s power use rather than those than last just a few seconds or minutes. “A sufficiently long power measurement (several minutes) enables the learning algorithm to ‘see’ through the noise,” the researchers write. “We show that measuring the phone’s aggregate power consumption over time completely reveals the phone’s location and #movement.”
Even so, PowerSpy has a major limitation: It requires that the snooper pre-measure how a phone’s power use behaves as it travels along defined routes. This means you can’t snoop on a place you or a cohort has never been, as you need to have actually walked or driven along the route your subject’s phone takes in order to draw any location conclusions.
I’m not sure how practical this is, but it’s certainly interesting.
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